Object predetection based on kernel parametric distribution fitting

Jean Philippe Tarel, Sabri Boughorbel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multimodal distribution fitting is an important task in pattern recognition. For instance, the predetection which is the preliminary stage that limits image areas to be processed in the detection stage amounts to the modeling of a multimodal distribution. Different techniques are available for such modeling. We propose a pros and cons analysis of multimodal distribution fitting techniques convenient for object predetection in images. This analysis leads us to propose efficient and accurate variants over the previously proposed techniques as shown by our experiments. These variants are based on parametric distribution fitting in the RKHS space induced by a positive definite kernel.

Original languageEnglish
Title of host publicationProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages808-811
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2006
Externally publishedYes
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Other

Other18th International Conference on Pattern Recognition, ICPR 2006
CountryChina
CityHong Kong
Period20/8/0624/8/06

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Tarel, J. P., & Boughorbel, S. (2006). Object predetection based on kernel parametric distribution fitting. In Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006 (pp. 808-811). [1699328] (Proceedings - International Conference on Pattern Recognition; Vol. 2). https://doi.org/10.1109/ICPR.2006.883